An electroencephalograph produces an encephalogram (EEG) to represent graphically brain waves representing electrical activity in the brain. The EEG can be used to diagnose neurological disorders. The electroencephalograph measures neural activity signals using a plurality of electrodes adhered to the scalp of the patient. Differences in electric potential between different parts of the brain are measured with multiple galvanometers and printed simultaneously as waveform tracings that have standard configurations in the normal brain. Variations from standard waveforms may be indicative of a brain disorder. Neural activity signals can also be captured, processed and analyzed to determine how well a patient sleeps.
Digital signal processing techniques may be applied to detect non-standard neural waveforms and sleep modes. For example, event related potentials, e.g. amplitude and peak latency measures, have been compared across EEG trials representing brain responses to sensory stimulations to map the event related potentials and the sensory events. Other digital signal processing techniques, the fundamentals of which were developed in the fields of electrical engineering and information theory, include time/frequency analysis and independent component analysis. More complex electroencephalograph capabilities are required to provide more complex analysis. Equipment and analysis costs may be proportional to the complexity of the systems required to perform the analysis.